Artificial Neural Network for Production of Antioxidant Peptides Derived from Bighead Carp Muscles with Alcalase
2006
Lin Li | Jinshui Wang | Mouming Zhao | Chun Cui | Yueming Jiang
Controlled enzymatic modification proteins are currently being used as good sources of bioactive protein ingredients, and hydrolysates derived from bighead carp muscles may serve as antioxidants through the control of the processing-related parameters. The antioxidant ability was evaluated with regard to the scavenging effect on free radical DPPH·, OH· and O2 ·–. Due to the robustness, fault tolerance, high computational speed and self--learning ability, artificial neural network (ANN) can be employed to build a predictive model for hydrolysis and optimize the hydrolysis variables: pH, temperature, hydrolysis time, muscle/water ratio and enzyme/substrate ratio (E/S) for the production of antioxidant peptides. Optimum conditions to achieve the maximum antioxidant ability were obtained. The hydrolysates, which scavenged most effectively the DPPH·, OH· and O2 ·–, were hydrolyzed for 4.8 h with an activity of alcalase of 4.8 AU/kg, for 6 h with 3.84 AU/kg and for 4.3 h with 4.8 AU/kg, at pH=7.5 and 60 °C. Their respective muscle/water ratio was 1:1.9, 1:1.4 and 1:1. The present study confirmed that ANN could be used to simulate the hydrolysis process and predict hydrolysis conditions under which the hydrolysates could show the most effective scavenging ability on DPPH·, OH· and O2 ·–.
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